scholarly journals Analisis Risiko Finansial Dengan Metode Simulasi Monte Carlo (Studi Kasus: Pt. Phase Delta Control)

2016 ◽  
Vol 8 (1) ◽  
pp. 62
Author(s):  
Atikah Aghdhi Pratiwi ◽  
Rosa Rilantiana
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Historical Data ◽  
Uncertain Variable ◽  
Random Numbers ◽  
Selling Price ◽  
Sales Volume ◽  
Simulation Research ◽  
Cost Of Production ◽  
A Company

AbstractBasically, the purpose of a company is make a profit and enrich the owners of the company. This is manifested by development and achievement of good performance, both in financial and operational perspective. But in reality, not all of companies can achieve good performance. One of them is because exposure of risk. This could threaten achievement of the objectives and existence of the company. Therefore, companies need to have an idea related to possible condition and financial projection in future periods that are affected by risk. One of the possible method is Monte Carlo Simulation. Research will be conducted at PT. Phase Delta Control with historical data related to production/sales volume, cost of production and selling price. Historical data will be used as Monte Carlo Simulation with random numbers that describe probability of each risk variables describing reality. The main result is estimated profitability of PT. Phase Delta Control in given period. Profit estimation will be uncertain variable due to some uncertainty

D. Perhitungan HPP Telur Asin Dengan Pendekatan Variabel Costing Pada UD Mulya Jaya

2019 ◽  
Vol 4 (1) ◽  
pp. 30
Author(s):  
Neno Pratiwi ◽  
Andre Setiawan ◽  
Ilmi Cayono ◽  
Johan Trinanto
Keyword(s):  
Decision Making ◽  
Production Process ◽  
Raw Materials ◽  
Selling Price ◽  
Assistance Program ◽  
Total Cost ◽  
Cost Of Production ◽  
The Cost ◽  
A Company ◽  
Important Objective

ABSTRAK Pada umumnya harga pokok produksi dalam akuntansi diartikan dengan jumlah biaya dari seluruh pemakaian yang telah dilakukan selama proses produksi atau kegiatan yang mana mengubah bahan baku menjadi produk jadi (produk siap pakai/siap saji). Tujuan penting dalam tugas ini yaitu memperhitungkan harga pokok produksi dari UD Mulya Jaya dengan menggunakan pendekatan variabel costing untuk mengetahui besarnya harga pokok pada setiap produk yang diproduksi. Pentingnya penentuan harga pokok produksi dapat dilakukan sebelum para usaha menentukan harga jual. Pendampingan ini bertujuan untuk membantu mencari dan menentukan harga pokok produksi yang dapat digunakan untuk menetapkan harga jual. Pendampingan ini dilakukan untuk membantu wirausaha dalam program kerja, yaitu bimbingan akuntansi dengan fokus perhitungan harga pokok produksi. Dalam menentukan harga pokok produksi pada UD Mulya Jaya dapat menggunakan pendekatan variable costing yang biasanya metode ini digunakan untuk semacam pengambilan keputusan dalam perusahaan. Melalui program pendampingan kewirausahaan didapatkan hasil perhitungan harga pokok produksi yang menggunakan pendekatan variabel costing. Hasil tersebut dapat menjadi suatu keputusan bagi UD Mulya Jaya untuk dapat menetapkan harga pokok produksi pada setiap produk telur asin. Kata Kunci : Kewirausahaan, HPP, Harga.   ABSTRACT In general, the cost of production in accounting is defined as the total cost of all uses that have been made during the production process or activities which convert raw materials into finished products (ready-to-use / ready-to-serve products). An important objective in this task is to calculate the cost of goods manufactured from UD Mulya Jaya by using a variable costing approach to find out the cost of goods on each product produced. The importance of determining the cost of production can be done before businesses determine the selling price. This assistance aims to help find and determine the cost of production that can be used to set the selling price. This assistance is carried out to help entrepreneurs in work programs, namely accounting guidance with a focus on calculating the cost of production. In determining the cost of production at UD Mulya Jaya, it can use the variable costing approach, which is usually used for a kind of decision making in a company. Through the entrepreneurship assistance program, the results of the calculation of the cost of production are obtained using the variable costing approach. These results can be a decision for UD Mulya Jaya to be able to set the cost of production for each salted egg product. Keywords: Entrepreneurship, COGS, Price

Investigation of contribution of number of trials in Monte Carlo simulation for uncertainty estimation for a pressure balance

2021 ◽  
pp. 014233122110390
Author(s):  
Jasveer Singh ◽  
Neha Bura ◽  
Kapil Kaushik ◽  
Lakshmi Annamalai Kumaraswamidhas ◽  
Nita Dilawar Sharma
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Measurement Uncertainty ◽  
Critical Factor ◽  
Random Number Generation ◽  
Effective Area ◽  
National Physical Laboratory ◽  
Conventional Technique ◽  
Random Numbers ◽  
Pressure Balance

It is well established that the estimation of measurement uncertainty is vital for the validation of any measurement and is an essential parameter of quality assurance. Apart from the conventional technique of law of propagation of uncertainty (LPU), which has many limitations, Monte Carlo simulation (MCS) technique has become an essential tool for the estimation of measurement uncertainty in various fields of metrology. The most critical factor in MCS is the generation of random numbers of the input quantities according to their probability distributions. The number of Monte Carlo trials to generate these random numbers significantly affects the results. In particular, the required number of trials is also affected by the parameter for which the uncertainty is to be estimated. Hence, in the current paper, the effect of selection of the number of trials on the random number generation and the resulting output in terms of standard deviation (SD) is investigated for the uncertainty in the effective area of a pneumatic reference pressure standard (NPLI-4) at the CSIR-National Physical Laboratory of India. The simulation results thus obtained are compared amongst themselves, with an adaptive approach as well as with the experimental results. The outcomes are analyzed and discussed in detail.

scholarly journals Fuzzy-Based Multivariate Analysis for Input Modeling of Risk Assessment in Wind Farm Projects

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 325
Author(s):  
Emad Mohamed ◽  
Parinaz Jafari ◽  
Simaan AbouRizk
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Wind Farm ◽  
Historical Data ◽  
Expert Knowledge ◽  
Bivariate Distribution ◽  
Expert Elicitation ◽  
Illustrative Case ◽  
Input Modeling

Currently, input modeling for Monte Carlo simulation (MSC) is performed either by fitting a probability distribution to historical data or using expert elicitation methods when historical data are limited. These approaches, however, are not suitable for wind farm construction, where—although lacking in historical data—large amounts of subjective knowledge describing the impacts of risk factors are available. Existing approaches are also limited by their inability to consider a risk factor’s impact on cost and schedule as dependent. This paper is proposing a methodology to enhance input modeling in Monte Carlo risk assessment of wind farm projects based on fuzzy set theory and multivariate modeling. In the proposed method, subjective expert knowledge is quantified using fuzzy logic and is used to determine the parameters of a marginal generalized Beta distribution. Then, the correlation between the cost and schedule impact is determined and fit jointly into a bivariate distribution using copulas. To evaluate the feasibility of the proposed methodology and to demonstrate its main features, the method was applied to an illustrative case study, and sensitivity analysis and face validation were used to evaluate the method. The results demonstrated that the proposed approach provides a reliable method for enhancing input modeling in Monte Carlo simulation (MCS).

Assessing Curriculum Efficiency Through Monte Carlo Simulation

2018 ◽  
Vol 22 (4) ◽  
pp. 597-610
Author(s):  
David Torres ◽  
Jorge Crichigno ◽  
Carmella Sanchez
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Frequency Distribution ◽  
Relative Frequency ◽  
Monte Carlo Algorithm ◽  
Pass Rate ◽  
Random Numbers ◽  
Pass Rates ◽  
Low Pass ◽  
Relative Frequency Distribution

A Monte Carlo algorithm is designed to predict the average time to graduate by enrolling virtual students in a degree plan. The algorithm can be used to improve graduation rates by identifying bottlenecks in a degree plan (e.g., low pass rate courses and prerequisites). Random numbers are used to determine whether students pass or fail classes by comparing them to institutional pass rates. Courses cannot be taken unless prerequisites and corequisites are satisfied. The output of the algorithm generates a relative frequency distribution which plots the number of students who graduate by semester. Pass rates of courses can be changed to determine the courses that have the greatest impact on the time to graduate. Prerequisites can also be removed to determine whether certain prerequisites significantly affect the time to graduate.

scholarly journals SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD

2017 ◽  
Vol 7 (4) ◽  
pp. 20-23
Author(s):  
Tomasz Rymarczyk ◽  
Grzegorz Kłosowski
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Supply Chain ◽  
Cost Estimation ◽  
Historical Data ◽  
Supply Chain Risk Management ◽  
Supply Chain Risk ◽  
Chain Management

In this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.

scholarly journals Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS

2021 ◽  
pp. 134-138
Author(s):  
Faisal Roza ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Probability Distribution ◽  
Civil Servant ◽  
Random Numbers ◽  
Basic Training ◽  
Internal Affairs

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.

Financial viability for milk production of Dutch and Jersey breeds: An analysis through Monte Carlo simulation and Sensitivity Analysis

2016 ◽  
Vol 9 (2) ◽  
pp. 130
Author(s):  
Evelin Gonçalves Suchla ◽  
Anderson Catapan ◽  
Edilson Antonio Catapan ◽  
Rafael Klüppel Smijtink
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Milk Production ◽  
Cash Flows ◽  
Financial Viability ◽  
Selling Price ◽  
Variable Parameters

Due to the favorable characteristics such as climate and topography, the Agribusiness represents much of the generation of wealth in Brazil. Considering this importance, the objective of this research was to identify how many cows of the Dutch and Jersey breeds are required for a small milk producer get profit with its production of Brazilian. For this, the cash flows and the NPV were calculated. The NPV was calculated under deterministic and probabilistic aspects, performing a Monte Carlo simulation and afterwards a Sensitivity Analysis, illustrating the variable parameters that more influence in the outcome of the NPV. It was noticed that the selling price of a liter of milk and the amount of liters of milk produced per cow are the parameters which most affect the NPV. The results showed that there is a need for at least 33 cows of Dutch breed or 43 cows of Jersey breed for the project to generate wealth to the producer

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